Igor Douven

External world skeptics are typically opposed to admitting as evidence anything that goes beyond the purely phenomenal, and equally typically, they disown the use of rules of inference that might enable one to move from premises about the phenomenal alone to a conclusion about the external world. This seems to bar any a posteriori resolution of the skepticism debate. This paper argues that the situation is not quite so hopeless, and that an a posteriori resolution of the debate becomes possible once it is recognized that the skeptic holds overly defensive and ill-motivated positions vis-à-vis both evidence and inference, and that more reasonable ones are available. In stating these more reasonable positions, as well as in showing how they make possible an a posteriori resolution of the skepticism debate, the paper draws on the machinery of Bayesian epistemology.

The Lottery Paradox and the Preface Paradox both involve the thesis that high probability is sufficient for rational acceptability. The standard solution to these paradoxes denies that rational acceptability is deductively closed. This solution has a number of untoward consequences. The present paper suggests that a better solution to the paradoxes is to replace the thesis that high probability suffices for rational acceptability with a somewhat stricter thesis. This avoids the untoward consequences of the standard solution. The new solution will be defended against a seemingly obvious objection. 1 The paradoxes of rational acceptability 2 The standard solution 3 A new solution to the paradoxes 4 Basic assumptions 5 The new solution defended 6 Conclusion 7 Appendix.

This paper is concerned with formal solutions to the lottery paradox on which high probability defeasibly warrants acceptance. It considers some recently proposed solutions of this type and presents an argument showing that these solutions are trivial in that they boil down to the claim that perfect probability is sufficient for rational acceptability. The argument is then generalized, showing that a broad class of similar solutions faces the same problem. An argument against some formal solutions to the lottery paradox The argument generalized Some variations Adding modalities Anticipated objections.

In recent years, various computational models have been developed for studying the dynamics of belief formation in a population of epistemically interacting agents that try to determine the numerical value of a given parameter. Whereas in those models, agents’ belief states consist of single numerical beliefs, the present paper describes a model that equips agents with richer belief states containing many beliefs that, moreover, are logically interconnected. Correspondingly, the truth the agents are after is a theory (a set of sentences of a given language) rather than a numerical value. The agents epistemically interact with each other and also receive evidence in varying degrees of informativeness about the truth. We use computer simulations to study how fast and accurately such populations as wholes are able to approach the truth under differing combinations of settings of the key parameters of the model, such as the degree of informativeness of the evidence and the weight the agents give to the evidence

It is widely believed that the so-called knowledge account of assertion best explains why sentences such as “It’s raining in Paris but I don’t believe it” and “It’s raining in Paris but I don’t know it” appear odd to us. I argue that the rival rational credibility account of assertion explains that fact just as well. I do so by providing a broadly Bayesian analysis of the said type of sentences which shows that such sentences cannot express rationally held beliefs. As an interesting aside, it will be seen that these sentences also harbor a lesson for Bayesian epistemology itself.

According to the deontological view on justification, being justified in believing some proposition is a matter of having done one's epistemic duty with respect to that proposition. The present paper argues that, given a proper articulation of the deontological view, it is defensible that knowledge is justified true belief, pace virtually all epistemologists since Gettier. One important claim to be argued for is that once it is appreciated that it depends on contextual factors whether a person has done her epistemic duty with respect to a given proposition, many so-called Gettier cases, which are supposed to be cases of justified true belief that are not cases of knowledge, will be seen to be not really cases of justified belief after all. A second important claim is that the remaining alleged Gettier cases can be qualified as cases of knowledge. This requires that we countenance a notion of epistemic luck, but the requisite kind of luck is of a quite benign nature.

According to Putnam the reference of natural kind terms is fixed by the world, at least partly; whether two things belong to the same kind depends on whether they obey the same objective laws. We show that Putnam's criterion of substance identity only "works" if we read "objective laws" as "OBJECTIVE LAWS". Moreover, at least some of the laws of some of the special sciences have to be included. But what we consider to be good special sciences and what not depends upon our values. Hence, "objective laws" cannot be read as "OBJECTIVE LAWS". It follows that the reference of natural kind terms cannot be fixed by the world, not even partly. The final conclusion applies to a variety of realisms

According to van Fraassen, constructive empiricism yields a better account of science than does scientific realism. One particularly important advantage van Fraassen claims his position to have over scientific realism is that the former can make sense of science without invoking pre-Kantian metaphysics. In the present paper the consistency of van Fraassen's position is put in doubt. Specifically, it will be argued that van Fraassen faces the paradox that he cannot do with nor without the pre-Kantian metaphysics he abhors.

Inductive logics purport to specify, for any given hypothesis and any given evidence statement, whether and, if so, to what extent the evidence statement should bear on our confidence that the hypothesis is true. If we agree that there can only be one true answer to questions of this sort, then the project of inductive logic faces a serious difficulty, namely that the many different systems that have been proposed in the literature rarely reach an unanimous verdict. In this paper I investigate the possibility of settling empirically the question which of all the extant inductive logics is the correct one, or, if the correct inductive logic should still await formulation, which of the extant inductive logics is the least incorrect. My main point will be that the fact that empirical investigation of inductive logics necessarily requires the use of some inductive logic at the metalevel does not render the whole project futile. I also discuss and eventually dismiss some well-known Bayesian arguments to the effect that the debate about the correct inductive logic can be settled on a priori grounds and has in fact been settled in favour of Bayesianism

Adams famously suggested that the acceptability of any indicative conditional whose antecedent and consequent are both factive sentences amounts to the subjective conditional probability of the consequent given the antecedent. The received view has it that this thesis offers an adequate partial explication of Ramsey’s test, which characterizes graded acceptability for conditionals in terms of hypothetical updates on the antecedent. Some results in van Fraassen may raise hope that this explicatory approach to Ramsey’s test is extendible to left-nested conditionals, that is, conditionals whose antecedent is itself conditional in form. We argue that this interpretation of van Fraassen’s results is to be rejected. Specifically, we provide an argument from material inadequacy against a generalization of Adams’ thesis for left-nested conditionals

According to Stalnaker’s Hypothesis, the probability of an indicative conditional, $\Pr(\varphi \rightarrow \psi),$ equals the probability of the consequent conditional on its antecedent, $\Pr(\psi | \varphi)$ . While the hypothesis is generally taken to have been conclusively refuted by Lewis’ and others’ triviality arguments, its descriptive adequacy has been confirmed in many experimental studies. In this paper, we consider some possible ways of resolving the apparent tension between the analytical and the empirical results relating to Stalnaker’s Hypothesis and we argue that none offer a satisfactory resolution

In a famous critique, Goodman dismissed similarity as a slippery and both philosophically and scientifically useless notion. We revisit his critique in the light of important recent work on similarity in psychology and cognitive science. Specifically, we use Tversky’s influential set-theoretic account of similarity as well as Gärdenfors’s more recent resuscitation of the geometrical account to show that, while Goodman’s critique contained valuable insights, it does not warrant a dismissal of similarity

Earman (1993) distinguishes three notions of empirical indistinguishability and offers a rigorous framework to investigate how each of these notions relates to the problem of underdetermination of theory choice. He uses some of the results obtained in this framework to argue for a version of scientific anti- realism. In the present paper we first criticize Earman's arguments for that position. Secondly, we propose and motivate a modification of Earman's framework and establish several results concerning some of the notions of indistinguishability in this modified framework. Finally, we interpret these results in the light of the realism/anti- realism debate.

There is good reason to believe that, if it can be decided at all, the realism debate must be decided on a posteriori grounds. But at least prima facie the prospects for an a posteriori resolution of the debate seem bleak, given that realists and antirealists disagree over two of the most fundamental questions pertaining to any kind of empirical research, to wit, what the range of accessible evidence is and what the methodological status of explanatory considerations is. The present paper aims to show that, while the difficulties that face an empirical approach to the realism debate are not to be discounted, they are not insurmountable either. Specifically, it presents a broadly Bayesian strategy for resolving the debate that is capable of solving those difficulties. The strategy crucially involves answers to the aforementioned questions that diverge from both the standard realist and the standard antirealist answers, but that should appear more natural and plausible than those to realists and antirealists alike.